Filters: partyWithName: U.S. Geological Survey - ScienceBase (X) > Categories: Data Release - Revised (X)
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A monthly water balance model (MWBM) was driven with precipitation and temperature using a station-based dataset for current conditions (1949 to 2010) and selected statistically-downscaled general circulation models (GCMs) for current and future conditions (1950 to 2099) across the conterminous United States (CONUS) using hydrologic response units from the Geospatial Fabric for National Hydrologic Modeling (Viger and Bock, 2014). Six MWBM output variables (actual evapotranspiration (AET), potential evapotranspiration (PET), runoff (RO), streamflow (STRM), soil moisture storage (SOIL), and snow water equivalent (SWE)) and the two MWBM input variables (atmospheric temperature (TAVE) and precipitation (PPT)) were summarized...
Categories: Data,
Data Release - Revised;
Types: Map Service,
NetCDF OPeNDAP Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: USGS Science Data Catalog (SDC),
United States,
Water Resources,
hydrology,
inlandWaters,
Lidar-derived digital elevation models often contain a vertical bias due to vegetation. In areas with tidal influence the amount of bias can be ecologically significant, for example, by decreasing the expected inundation frequency. We generated a corrected digital elevation mode (DEM) for Suisun marsh using a modification of the Lidar Elevation Adjustment with NDVI (LEAN) technique (Buffington et al. 2016). GPS survey data (6912 points, collected across public and private land in 2018), Normalized Difference Vegetation Index (NDVI) derived from an airborne multispectral image (June 2018), a 1 m lidar DEM from September 2018, and a 1 m canopy surface model were used to generate models of predicted bias across the...
Dataset includes publicly available geologic and rainfall data, and environmental and ecological data derived or collected for this project. Specifically, water infiltration measurements, interepreted field-saturated hydraulic conductivity values, ungulate activity, vegetation cover, general soil and weather conditions data are included. Soil samples were collected, lab analyzed, and are included in the dataset. Field-collected data are associated with plots that encompassed approximately a 3 x 3 m area; site data represent approximately 20 x 20 m. First posted: 4 March 2020 (available from author) Revised: April 13, 2020 (version 2.0) The revision is provided due to minor refinement of the dataset and updated...
Categories: Data,
Data Release - Revised;
Tags: Hawaii,
Hedychium gardnerianum,
Kauai,
Metrosideros polymorpha,
USGS Science Data Catalog (SDC),
Sleeper populations are established populations of introduced species whose population growth is limited by one or more abiotic or biotic conditions. Sleeper populations pose an invasion risk if a change in those limiting conditions, such as climate change, enables population growth and invasion. With thousands of established species, it is critical that we identify and prioritize potential sleepers. Here, we identified non-native plants established in the northeastern United States with high impacts and the potential to expand with climate change. We focused on 118 taxa regulated by one or more state outside the Northeast plus 61 taxa recorded as invasive globally and under consideration for regulation in the Northeast....
Categories: Data,
Data Release - Revised;
Tags: Northeast United States,
USGS Science Data Catalog (SDC),
biota,
climate change,
invasive plants,
Note: this data release has been deprecated. Please see new data release here: https://doi.org/10.5066/P1WOQBRN. The U.S. Inland Creel and Angler Survey Catalog (CreelCat) contains data compiled from 14,729 creel and angler surveys conducted by state natural resource management agencies (including Washington DC and Puerto Rico) in inland waters across the United States. Data is are contained in eight .csv files which contain information about survey characteristics (Survey_Data.csv), angler effort (AngEffort_Data.csv), catch and harvest (FishDataCompiled.csv), angler demographics (Demographic_Data.csv), angler preferences (AngPrefDataCompiled.csv), taxonomic classifications (Taxa_Data.csv), issues with catch and...
Categories: Data Release - Revised;
Tags: Aquatic Biology,
United States,
biota,
fish,
fisheries management,
This data consists of observations of individual trees that were subjected to prescribed fire in western US national parks. Information on individual trees include measurements of tree live/dead status, growth, size, competition, and fire-caused damage. The data also includes estimates of plot-level vapor pressure deficit anomaly before fire. These data support the following publication: van Mantgem, P.J., Falk, D.A., Williams, E.C., Das, A.J., and Stephenson, N.L., 2020, The influence of pre-fire growth on post-fire tree mortality for common conifers in western US parks. International Journal of Wildland Fire. First posted - August 28, 2018 (available from author) Revised - Febuary 10, 2020
The U.S. Geological Survey (USGS) has developed the PRObability of Streamflow PERmanence (PROSPER) model, a GIS raster-based empirical model that provides streamflow permanence probabilities (probabilistic predictions) of a stream channel having year-round flow for any unregulated and minimally-impaired stream channel in the Pacific Northwest region, U.S. The model provides annual predictions for 2004-2016 at a 30-m spatial resolution based on monthly or annually updated values of climatic conditions and static physiographic variables associated with the upstream basin (Raw streamflow permanence probability rasters). Predictions correspond to pixels on the channel network consistent with the medium resolution National...
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